Image Captioning: reading plan
Overview
This repository contains a working research note about Image Captioning. It organizes motivation, related work, a falsifiable hypothesis, and an evaluation plan. It is not presented as a completed paper or a release of trained models.
Changelog
- 2026-10-07 — initial upload
- 2026-10-21 — config and docs sync
Scope and limitations
Exploratory by design: no benchmark claims, no completed ablations, no released code, no trained checkpoint. The references are a starting point for verification, not evidence that the study has run.
Roadmap
Next steps, in no particular order: a cleaner entry point, input-shape docs, and a small evaluation script if time permits.
Related work
A reading list around Image Captioning is being assembled. Entries will be added as the note matures; suggestions via repository discussions are welcome.
Open questions
- which baselines are actually comparable under matched capacity?
- what is the minimum data exposure for a meaningful signal?
- which confounders would invalidate a naive comparison?
What is covered
- the scope of the research question and likely confounders
- a proposed comparison with matched baselines
- concrete evaluation context such as MS COCO Captions, NoCaps, and TextCaps
- reproducibility checks, failure modes, and open questions
- topic-relevant references
Files
summary.md— primary artifactREADME.md— this documentationconfig.json— architecture configurationtraining_args.json— default experiment settingsmodel.safetensors— initialization checkpoint
License
Released under mit. Review the source-data terms separately when this repository is used with external datasets.
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